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Patricia Lichtenstein

Bio

As a student and researcher in cognitive linguistics, Trish is primarily occupied in the study of the nature of linguistic behavior and its relationship to other aspects of human cognition. Her primary areas of interest include linguistic behavior as an incidence of emergent structure, and meaning as an incidence of embodied experience. Her path to these areas of interest has its source in a fascination with language and cognition and the ways in which language and thought seem to feed into one another in a process that enriches both. Much of her academic career—at the University of Chicago, the London School of Economics, Duke University, and Case Western Reserve University—has been spent in pursuit of understanding the relation between language and thought, with a concentration in some instances on linguistics and the formal properties of language, and in other instances, on philosophy and the theoretical properties of thought. At this stage in her career, she has come to believe very strongly in the cognitive science approach toward an integrative study of brain, behavior, and the developmental forces shaping them. She also believes quite passionately in the promise of A New Kind of Science helping us understand human cognition to a greater extent than heretofore possible.

Project: A Simple Rule to Describe Meaning-Preserving Transformations of Word Order

How prevalent are meaning-preserving transformations in natural language?

Consider the word, which is the most basic grammatical construction in English, and also consider synonymy, which is the most commonly applied meaning-preserving transformation at the level of the word. There are c. 600,000 words in English. There are on average 16 synonyms per word in English.

Now consider a more complex construction, such as the passive. At this level, potential meaning-preserving transformations are relatively sparse. Subj aux VPpp (PPby) ---> Subj V Obj

Suppose an intermediate strategy were to be implemented, in which word form is preserved, grammatical constructions are ignored, and the only transformations to be applied are changes to word order. For example, PP Det N ---> N PP Det

The experiment conducted in this project tests the success of such a strategy at preserving meaning, where success is defined in terms of the frequency with which different permutations of word order appear in a natural language corpus.